[unreadable] [unreadable] Differences in the expression of several genes between normal brain and its tumors (such as glioma) can provide information useful for malignant glioma diagnosis and therapy. Gliomas arise in the brain and are characterized by heterogeneous regions of necrosis, apoptosis, proliferation, invasion and angiogenesis. Drugs are being developed to target such phenotypes but it is unclear what imaging or molecular correlate will such drugs use to assay responses. Recently, serial analysis of gene expression (SAGE) data for malignant glioma has become available through efforts of the Cancer Genome Anatomy Project (CGAP) and several genes have been identified that are over expressed in glioma and not in normal brain. Some of these genes have been postulated to correlate with a particular glioma phenotype, such as invasion or angiogenesis. We propose a set of technologies useful to translate CGAP's knowledge into imaging the transcriptional activation of these genes and correlate such activation with the observed phenotypic heterogeneity in in vitro and in vivo models. We plan to combine the ability of our infectious bacterial artificial chromosome (iBAC) technology to rapidly isolate and deliver into cells large genomic fragments (up to 150 kb) with the ability of MRI and bioluminescence imaging to image gene expression. Specifically, the R21 phase this project proposes to: 1- Verify that large 5' flanking regions of one glioma expressed gene (for SPARC) transcriptionally activates the MRI-imaging gene ETR and luciferase, 2- Image the transcriptional activation of this region in in vitro models of glioma, 3- Image the transcriptional activation of this region in in vivo models of glioma. Transgenic mouse models have shown that large regions of 5' flanking area are best at providing complex tissue-specific and developmentally correct gene expression. A large 5' flanking region of SPARC will thus be cloned upstream of luciferase and/or ETR in the iBAC system. Imaging will be performed in in vitro and in vivo glioma models. The information obtained in this R21 will justify further grants (R33, R01) where the transcriptional activation of other genes can be imaged, thus providing a quantitative anatomic map of transcriptional activation in different heterogeneous regions of gliomas (invading, angiogenic, hypoxic, proliferating areas). This provides a baseline for assessing the effects of therapies (drugs, radiation) on these tumor phenotypes. The conceptual scheme presented herein will also be applicable to a variety of diseases for which gene profiling analyses are available. [unreadable] [unreadable]